Shared-memory parallel multi-target tracking
共享存储并行多目标跟踪

The application of particle filtering in real video-based multi-target tracking systems is limited because of its high computational complexity. To overcome the efficiency bottleneck, a coarse-grained parallel multi-target tracking implementation based on the OpenMP-specified shared-memory parallel programming model was explored. A list of tracked targets was maintained in a shared variable, and each target was tracked by an independent particle filter. The number of threads and the number of targets tracked by each thread were determined by the number of processing units. Compared to its corresponding optimized sequential version, the parallel implementation, which increases the number of targets in real-time tracking from 2 to 8, is of much more practical value.